The present paper highlights the methodology and results of agricultural biomass estimation in Haryana using geo-informatics and conventional surveys for power generation. Multi-date and multi-season Indian Remote Sensing Satellite (IRS) LISS-3 digital data of 23.5 m spatial resolution along with various spatial and non-spatial collateral data have been used to generate total cropped area (Monsoon and Winter season). Harvest Indices (HI) values of various crops and average yield data were used to assess crop wise total agricultural biomass, total non-grain (NG)/non-economic (NE) agricultural biomass. Surplus agricultural biomass available for power generation was calculated using the field survey in about 200 village locations. The crop-wise biomass requirement for generation of 1 MW electrical power for 6500 hrs in a year was used as available in literature. In Haryana district-level power generation potential was computed using the availability of crop-wise surplus agricultural biomass. The net surplus biomass available after the domestic use and subtraction of crops biomass used as fodder and selling by the farmers is 8416.47 thousand tonnes. The total power generation potential from this biomass is 1018.95 MW. It is expected that the maps and data will help in selecting suitable sites for setting up of small power generation plants using surplus agricultural biomass.

Identification and demarcation of Forest lands on the ground remains a major challenge in Forest administration and management. Cadastral forest mapping deals with forestlands boundary delineation and their associated characterization (forest/non forest). The present study is an application of high resolution World View-II data for digitization of Protected Forest boundary at cadastral level with integration of Records of Right (ROR) data. Cadastral vector data was generated by digitization of spatial data using scanned mussavies in ArcGIS environment. Ortho-images were created from World View-II digital stereo data with Universal Transverse Mercator coordinate system with WGS 84 datum. Cadastral vector data of Bir Hisar (Hisar district, Haryana) and adjacent villages was spatially adjusted over ortho-image using ArcGIS software. Edge matching of village boundaries was done with respect to khasra boundaries of individual village. The notified forest grids were identified on ortho-image and grid vector data was extracted from georeferenced cadastral data. Cadastral forest boundary vectors were digitized from ortho-images. Accuracy of cadastral data was checked by comparison of randomly selected geo-coordinates points, tie lines and boundary measurements of randomly selected parcels generated from image data set with that of actual field measurements. Area comparison was done between cadastral map area, the image map area and RoR area. The area covered under Protected Forest was compared with ROR data and within an accuracy of less than 1 % from ROR area was accepted. The methodology presented in this paper is useful to update the cadastral forest maps. The produced GIS databases and large-scale Forest Maps may serve as a data foundation towards a land register of forests. The study introduces the use of very high resolution satellite data to develop a method for cadastral surveying through on - screen digitization in a less time as compared to the old fashioned cadastral parcel boundaries surveying method.

Agriculture resources reflected to be one of the most imperative renewable and dynamic natural resources. Agricultural sustainability has the premier priority in all countries, whether developed or developing. Cropping system analysis is indispensable for grinding the sustainability of agricultural science. Crop alternation is stated as growing one crop after another on the same piece of land in altered timings (seasons) without prejudicing the soil fertility. The study has been conducted for Fatehabad district of Haryana State of Indo-Gangetic plains in India. This paper generated cropping pattern and crop rotation maps of Fatehabad district. Multi-date IRS LISS-III digital data of different cropping seasons of 2007-08 have been used for this study. The present study relies on data from remote sensing combined with ground observations. Multi-date images of Rabi season images were geo-referenced using master images. Multi-date images of Kharif and single date image of summer seasons were geo-referenced with geo-referenced Rabi season image using image-to-image registrations and nearest neighborhood resampling method was applied. Multilayer stack were prepared for Kharif and Rabi cropping seasons. Stacked images of different seasons were classified using complete enumeration approach and unsupervised ISO-Data clustering classifier with district outside and non-agriculture mask based on some defined conditions such as the number of clusters, threshold, and number of iterations etc. A multiphased unsupervised ISODATA classification was used for seasonal cropping pattern mapping. The results showed that in the area, a monophonic crop pattern was found in summer and major part of the district is lying as fallow and major crops are fodder, dhaicha & sunflower, but in winter, areas under dissimilar crop pattern had changed melodramatically.

Desertification constitutes one of the international environment problems whose global importance has been recognized by the international community. Desertification is a problem that affects a number of regions of the world in the developed and developing countries. Desertification is even more closely associated with the development process insofar as it impacts on peoples livelihoods much more directly than other environmental problem. One of the central challenges of environment management in the coming years, the loss of productive land is of major concern in a world where hundreds millions of individuals already go hungry today. Availability of remote sensing data from earth observation satellite and GIS techniques has made it convenient to map and monitor land use/land cover of desertification areas. In the present study Desertification Change analysis in Panchkula district Haryana was carried out by using LISS-III satellite data of 2002 and 2011. The main objective of the study was to monitor the changes in degraded lands in the district. Onscreen digitization technique was followed to interpret the satellite data. The two dates maps were overlaid and changes in area under various degraded lands were calculated. It was observed that Total geographical area of under investigation is 1021.86 sq. km.

The present paper describes the methodology and results of assessment of seasonal progress of rice stubble burning for 10 major rice growing districts of Haryana state in India. These 10 districts contribute about 84 per cent of total rice area of the state. As the rice fields are immediately required to be vacated for the sowing of next crop the farmers opt for mechanized harvesting and easy way out of burning the stubbles in the field. Such burning result in release of polluting gases and aerosols. Besides, the heating of the soil kills the useful micro-flora of the soil causing soil degradation. Multi-date AWiFS data from Resourcesat 1 and 2 satellites acquired between October 16, 2013 to November 26, 2013 were used for estimating paddy stubble burning areas at different intervals for the year 2013 crop growing season. In season collected ground truth data using hand held GPS along with field photographs were used to identify paddy stubble burning areas and other land features. Complete enumeration approach and Iterative Self-organizing Data Analysis Technique (ISODATA) unsupervised classifier was used for digital analysis. Normalized Difference Vegetation Index (NDVI) of each date was also used with other spectral bands of temporal images. To improve the classification accuracy the non-agricultural areas were masked out. The area was estimated by computing pixels under the classified image mask. Progress of paddy stubble burning was estimated at different intervals for the year 2013 using available cloud free multi-date IRS-P6 AWiFS data to identify the crucial period when stubbles burning takes place in major area so that preventive measures can be taken to curb the menace.

The significance of geoinformatics in groundwater exploration stems from the utility of satellite images in identifying and delineating various features like geomorphology, geology, lithology and hydrologic characteristics that may serve as direct or indirect indicators of the presence of ground water. This study establisheses the role of remote sensing, GIS and GPS for mapping and assessment of ground water prospect. The IRS-P6-LISS-III multi-spectral satellite data have been used for preparing ground water prospects map on 1 : 50,000 scale. The study area, Mahendergarh district, is located from 27°47' to 28°26' N latitude and 75°56' to 76°51' E longitude. The study area consists of 1939.13 sq. km area. Most area is covered by eolian plain. The major hydrogeomorphic units are hills (structural, denudational, residual), pediment, valley, dune complex, alluvial plain, eolian plain, flood plain, inselberg, sand dunes and lineament. After finalizing the spatial database and collecting the relevant information, a detailed analysis was carried out to demarcate the ground water prospects area. Overall, the ground water prospect of Mahendergarh district is very poor. Structural features found in this district are fault confirmed (minor), fracture/lineament confirmed, fracture/lineament inferred and trend line. The lineaments are trending in NE-SW direction. The structural feature map is highly useful for ground water prospects especially at intersection of lineaments.